Checking the features:

MSE: 3.0550680492414715e+26

The matches were doing by categorizing the states based on the xˉ±2sd(x)\bar{x}\pm 2 \cdot sd(x) for each feature

The ideal accuracy is by setting thresholds with higher sdsd and allowing it to meet higher criteria (ideally all)

The time stamps were categorised and the the forecasted values were compared against it [best so far]

Total number of states: 15805
Matched states : 11059; 	    Accuracy: 69.97%
Matched within 1 state: 11675; 	Accuracy within 1 state: 73.87%
unassigned : 3033,              Percentage : 19.19% 

The graph of the different features:

statsexchange_link